The Role of Novel Bladder Cancer Diagnostic and Surveillance Biomarkers-What Should a Urologist Really Know?

Treatment Modalities for Non-Muscle Invasive Bladder Cancer: An Updated Review

The landscape of treatment for non-muscle invasive bladder cancer is rapidly changing. A complete and careful transurethral resection is the mainstay of initial treatment and is followed by intravesical therapy in intermediate or high-risk cases. The standard of care is intravesical BCG. Many alternative or additive approaches to this are being explored. We divided this review into three relevant spaces to consider these novel treatment approaches: (1) low-risk disease, for which intravesical therapy is not usually considered, (2) BCG-naïve disease (i.e., considering alternatives to the standard therapy), and (3) BCG-unresponsive disease. We performed a review of published literature and summarized ongoing trials in the United States. Novel approaches that we explored include surgical techniques for resection, alterations in dwell time for intravesical therapy, delivery method and schedule of intravesical therapies, new intravesical therapy agents, and systemic therapies (especially immunotherapy). These are thoroughly outlined throughout this review article, and the numerous modalities being studied demonstrate significant promise for the future treatment of the expanding space of NMIBC.

Office-based management of Non-Muscle Invasive Bladder Cancer (NMIBC): A position paper on current state of the art and future perspectives

To the Editor, Bladder cancer is one of the most common cancers in humans, representing the 7th and 17th type of neoplasm in both genders. Its incidence and mortality are quite heterogeneous in different countries and are due to different risk factors, quality and prevalence of healthcare and the possibility of early diagnosis and treatment of the tumor and its potential recurrences [...].

Bladder Cancer and Artificial Intelligence: Emerging Applications

Bladder cancer is a common and heterogeneous disease that poses a significant burden to the patient and health care system. Major unmet needs include effective early detection strategy, imprecision of risk stratification, and treatment-associated morbidities. The existing clinical paradigm is imprecise, which results in missed tumors, suboptimal therapy, and disease progression. Artificial intelligence holds immense potential to address many unmet needs in bladder cancer, including early detection, risk stratification, treatment planning, quality assessment, and outcome prediction. Despite recent advances, extensive work remains to affirm the efficacy of artificial intelligence as a decision-making tool for bladder cancer management.

Use of Multiple Machine Learning Approaches for Selecting Urothelial Cancer-Specific DNA Methylation Biomarkers in Urine

Diagnosing urothelial cancer (UCa) via invasive cystoscopy is painful, specifically in men, and can cause infection and bleeding. Because the UCa risk is higher for male patients, urinary non-invasive UCa biomarkers are highly desired to stratify men for invasive cystoscopy. We previously identified multiple DNA methylation sites in urine samples that detect UCa with a high sensitivity and specificity in men. Here, we identified the most relevant markers by employing multiple statistical approaches and machine learning (random forest, boosted trees, LASSO) using a dataset of 251 male UCa patients and 111 controls. Three CpG sites located in ALOX5, TRPS1 and an intergenic region on chromosome 16 have been concordantly selected by all approaches, and their combination in a single decision matrix for clinical use was tested based on their respective thresholds of the individual CpGs. The combination of ALOX5 and TRPS1 yielded the best overall sensitivity (61%) at a pre-set specificity of 95%. This combination exceeded both the diagnostic performance of the most sensitive bioinformatic approach and that of the best single CpG. In summary, we showed that overlap analysis of multiple statistical approaches identifies the most reliable biomarkers for UCa in a male collective. The results may assist in stratifying men for cystoscopy.

Bladder cancer risk stratification with the Oncuria 10-plex bead-based urinalysis assay using three different Luminex xMAP instrumentation platforms

BACKGROUND

No single marker of bladder cancer (BC) exists in urine samples with sufficient accuracy for disease diagnosis and treatment monitoring. The multiplex Oncuria BC assay noninvasively quantifies the concentration of 10 protein analytes in voided urine samples to quickly generate a unique molecular profile with proven BC diagnostic and treatment-tracking utility. Test adoption by diagnostic and research laboratories mandates reliably reproducible assay performance across a variety of instrumentation platforms used in different laboratories.

METHODS

We compared the performance of the clinically validated Oncuria BC multiplex immunoassay when data output was generated on three different analyzer systems. Voided urine samples from 36 subjects (18 with BC and 18 Controls) were reacted with Oncuria test reagents in three 96-well microtiter plates on Day 1, and consecutively evaluated on the LED/image-based MagPix, and laser/flow-based Luminex 200 and FlexMap 3D (all xMAP instruments from Luminex Corp., Austin, TX) on Day 2. The BC assay uses magnetic bead-based fluorescence technology (xMAP, Multi-analyte profiling; Luminex) to simultaneously quantify 10 protein analytes in urine specimens [i.e., angiogenin (ANG), apolipoprotein E (ApoE), carbonic anhydrase IX (CA9), CXCL8/interleukin-8 (IL-8), matrix metalloproteinase-9 (MMP-9), matrix metalloproteinase-10 (MMP-10), serpin A1/alpha-1 anti-trypsin (A1AT), serpin E1/plasminogen activator inhibitor-1 (PAI-1), CD138/syndecan-1 (SDC1), and vascular endothelial growth factor-A (VEGF-A)]. All three analyzers quantify fluorescence signals generated by the Oncuria assay.

RESULTS

All three platforms categorized all 10 analytes in identical samples at nearly identical concentrations, with variance across systems typically < 5%. While the most contemporary instrument, the FlexMap 3D, output higher raw fluorescence values than the two comparator systems, standard curve slopes and analyte concentrations determined in urine samples were concordant across all three units. Forty-four percent of BC samples registered ≥ 1 analyte above the highest standard concentration, i.e., A1AT (n = 7/18), IL-8 (n = 5), and/or ANG (n = 2), while only one control sample registered an analyte (A1AT) above the highest standard concentration.

CONCLUSION

Multiplex BC assays generate detailed molecular signatures useful for identifying BC, predicting treatment responsiveness, and tracking disease progression and recurrence. The similar performance of the Oncuria assay across three different analyzer systems supports test adaptation by clinical and research laboratories using existing xMAP platforms.

TRIAL REGISTRATION

This study was registered at ClinicalTrials.gov as NCT04564781, NCT03193528, NCT03193541, and NCT03193515.

Bladder cancer risk stratification with the Oncuria 10-plex bead-based urinalysis assay using three different Luminex xMAP instrumentation platforms

Background

No single marker of bladder cancer (BC) exists in urine samples with sufficient accuracy for disease diagnosis and treatment monitoring. The multiplex Oncuria BC assay noninvasively quantifies the concentration of 10 protein analytes in voided urine samples to quickly generate a unique molecular profile with proven BC diagnostic and treatment-tracking utility. Test adoption by diagnostic and research laboratories mandates reliably reproducible assay performance across a variety of instrumentation platforms used in different laboratories.

Methods

We compared the performance of the clinically validated Oncuria BC multiplex immunoassay when data output was generated on three different analyzer systems. Voided urine samples from 36 subjects (18 with BC and 18 Controls) were reacted with Oncuria test reagents in three 96-well microtiter plates on Day 1, and consecutively evaluated on the LED/image-based MagPix, and laser/flow based Luminex 200 and FlexMap 3D (all xMAP instruments from Luminex Corp., Austin, TX) on Day 2. The BC assay uses magnetic bead-based fluorescence technology (xMAP, Multi-analyte profiling; Luminex) to simultaneously quantify 10 protein analytes in urine specimens [i.e., angiogenin (ANG), apolipoprotein E (ApoE), carbonic anhydrase IX (CA9), CXCL8/interleukin-8 (IL-8), matrix metalloproteinase-9 (MMP-9), matrix metalloproteinase-10 (MMP-10), serpin A1/alpha-1 anti-trypsin (A1AT), serpin E1/plasminogen activator inhibitor-1 (PAI-1), CD138/syndecan-1 (SDC1), and vascular endothelial growth factor-A (VEGF-A)].

Results

All three platforms categorized all 10 analytes in identical samples at nearly identical concentrations, with variance across systems typically <5%. While the most contemporary instrument, the FlexMap 3D, output higher raw fluorescence values than the two comparator systems, standard curve slopes and analyte concentrations determined in urine samples were concordant across all three units. Forty-four percent of BC samples registered ≥1 analyte above the highest standard concentration, i.e., A1AT (n=7/18), IL-8 (n=5), and/or ANG (n=2). In Controls, A1AT was higher in one sample.

Conclusion

Multiplex BC assays generate detailed molecular signatures useful for identifying BC, predicting treatment esponsiveness, and tracking disease progression and recurrence. The similar performance of the Oncuria assay across three different analyzer systems supports test adaptation by clinical and research laboratories using existing xMAP platforms.

Trial Registration

This study was registered at ClinicalTrials.gov as NCT04564781, NCT03193528, NCT03193541, and NCT03193515.

Classification of formalin-fixed bladder cancer cells with laser tweezer Raman spectroscopy

Bladder cancer is a common cancer that is relatively hard to detect at an early stage because of its non-obvious symptoms. It is known that bladder cells can be found in urine samples which potentially could be used for early detection of bladder cancer. Raman spectroscopy is a powerful non-invasive tool for accessing biochemical information of cells. Combined with laser tweezers, to allow isolation of single cells, Raman spectroscopy has been used to characterise a number of bladder cells that might be found in a urine sample. Using principal component-canonical variates analysis (PC-CVA) and k-fold validation, the results shows that the invasive bladder cancer cells can be identified with accuracy greater than 87%. This demonstrates the potential of developing an early detection method that identifies the invasive bladder cancer cells in urine samples.

Evaluation of IGF2, KRT14, and KRT20 as Urinary Biomarkers in Patients with Bladder Cancer

Background

Many researchers have tried to identify bladder cancer biomarkers to reduce the need for cystoscopy. The aim of this study was to identify and measure appropriate transcripts in patient urine to develop a non-invasive screening test.

Methods

From February 2020 to May 2022, 49 samples were obtained from Velayat Hospital, Qazvin University of Medical Sciences, Qazvin, Iran. Twenty-two samples were obtained from bladder cancer patients and 27 from bladder cancer-free subjects. RNA was extracted from participant samples, quantitative RT-PCR was performed, and TNP plots were used to assess IGF2 (NCBI Gene ID: 3481), KRT14 (NCBI Gene ID: 3861) and KRT20 (NCBI Gene ID: 54474) expression. For UCSC Xena analysis, Dataset ID: TCGA-BLCA was used to compare transitional cell carcinoma (TCC) and normal samples for survival rates.

Results

IGF and KRT14 were more greatly expressed in patient urine samples than in those of the normal group. However, KRT20 expression did not significantly differ between the two groups. IGF2 had 45.45 and 88.89% sensitivity and specificity, respectively, for detecting TCC in urine samples while KRT14 had 59 and 88.89% sensitivity and specificity, respectively. Also, these results infer that overexpression of IGF would be prognosticators of poor TCC outcomes.

Conclusion

Our study showed that IGF2 and KRT14 are overexpressed in bladder cancer patient urine, and IGF2 could be a potential biomarker for poor prognoses in TCC.